 TheCube at Hadoop Summit 2014 is brought to you by Anchor Sponsor, Hortonworks. We do Hadoop. And headline sponsor, WAN Disco. We make Hadoop invincible. Okay, welcome back everyone. We're here live at Hadoop Summit 2014. This is TheCube, our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the founder of SiliconANGLE. My co-host here is Jeff Kelly. The leading big data analyst in the industry is with Wikibon.org. Jeff, great show here. I'm excited to have our next guest, Abhimed, CEO of Trasada, a long-time CUBE alumni. And I think TheCube has been following these events from day one. And it was in 2009, WeCoin, data factories. You know, operating system, actual insights, real time, industrial revolution, and transformation. And we're here now, welcome back. Thank you. Thank you so much, always a pleasure. And you know, this is my highlight for any show. It's sitting down with you and Jeff, and talking the future. And I think clearing, finding the signal from the noise, as you say, it's what I'm going to borrow it for now. So I got to ask you. So we've been living this transformation vision we were talking about from day one. We saw it early. But as it played out, it's been interesting. You're seeing a couple things we had Rob Bearden on earlier about, talking about the massive size of the market. Jeff Kelly was the first analyst and firm to put out the first market sizing, 50 billion. That's just in Hadoop that he quoted. But now you look at around that, the construction around the big data. It's in the hundreds, and you know, you can argue trillions of dollars in value. And we talked about that. Look at what's played out, right? Cloudera essentially had their IPO. They're now a whole nother company doing great. They, people cashed out the employees, the founders, the VCs took money off the table. That's now off to the races of big company. Hortonworks still a growing startup, kicking ass. And then you have MapR doing well. You guys are doing well. Everyone's succeeding. So now we start talking about business outcomes. So where are we, Avi? Give us the straight scoop. What's going on in this market? I think, so first of all, what I want to say is it is refreshing to come back to Hadoop Summit. This is, I think, my seventh or eighth event. And my first event was 300 people. John kind of just got another setting it. And apparently there are 3,200 people at the summit. And no pun intended. Every single tech elephant we know is in this room, right behind us. So I think it's a very refreshing, I would say refreshing in a very positive light that the journey we started together in forecasting the future of data, right? Not the future of technology, but the future of data and how it empowers enterprises to redo what we've always said, business models is well underway. That that journey is completely underway. The question always comes back to where does the value sit? So you're absolutely right. We've had the initial ring of companies monetize the value of the revolution for themself, be it Cloudera, Hortonworks and some others. I think we've seen a culling of the initial ranks where the tool companies are either dying or no longer financially viable. And I think we're starting, so we've seen the starts of the early adopters in the enterprises, and you talk to them a lot, the practitioners finding incredibly relevant and transformative business value by taking data not just from one source or two sources, from multiple sources, combining it into what we call a data asset and solving problems that literally could not be solved before. And you've seen that in every single industry. I think that's what makes it interesting for Trusseda and your vision is the fact that companies who deliver a capability, a set of software, what we call predictive analytics applications that can help them redo their business model is where it sits. We came out and said with you that what's at stake isn't billions of dollars, it's trillions of dollars. And I think I read a report recently that said actually it's five trillion dollars. I think McKinsey wrote the report. What that means is we're not just redoing the database market. We're not redoing the BI market. We're not redoing the storage market. We are redoing the very fabric of what a bank, what a healthcare company, what a retailer looks like and how they solve problems and deliver solution for their customers. So it's incredibly exciting. So we've got some questions already on CrowdChat. Go to CrowdChat.net slash Hadoop Summit. It's pumping on all cylinders. You know we've been following our progress. We're excited by that new engagement container we have. Nice. It's a great container. I really like to get the data, active data. So Bert asked you what is the biggest issue holding up production Hadoop implementations today? Great question. I think the biggest thing holding back the industry today in general is the lack of business applications. The two of you always ask me the question and we've been asking this question of ourselves for three years now. That Abhi, you and me and Richard started a company three years ago to build business applications on Hadoop and Jeff's telling me he was on a panel today and they asked, so where are the apps? And the only thing that comes up is Trusada. I think a lack of business applications that are helping companies get actionable insight. Not fix security, not clean data. I'm actually disappointed that the biggest story at Hadoop Summit this year is data transformation. Data transformation is free. We give data cleaning, data curation, data parsing, software as part of our application bundle away for free. And if we have to regress in our dialogue in the ecosystem around the hottest thing is data transformation. Is this the wrong conversation to have? Because you cannot expect a business user to sit around and have a user-friendly tool to clean data. They expect clean data to get insight from. Before we get to the dirty data, clean data argument. So Mike Olson from Cloudera and the Cloudera CEO at the time said this is the big data application this is three years ago. It just never happened. So I asked Mike that question. He said analytics became the killer app. And the analytics was really what people focused in on. So, analysts have come and gone. It's there now, it's native, you got visualization. What's next? So you guys are really one of the only ones out there with the app. So what will the apps look like? What does an app builder need to do? What is available? Is the platform available? What, how do you see the app market getting going? It's a fantastic question. As we have ruminated over this particular question over three years, what we've realized is something one of our customers told us. So we asked him and said what is it that we did for you when you use our applications in the payments area that you could not have done before? And the answer was fascinating. The person took me back to the graduation of a economy. How we used to be agrarian, then it became manufacturing and then it became services, right? And he says the next generation of what technologies do is take manual business processes and automate it. So a great example would be fraud. Fraud is a fantastic example. Fraud today in a particular scenario, actually let's be more specific, anti-money laundering in a specific scenario is a monumental human challenge. Typically there'll be 4,000 people sitting in a middle office looking at tickets around is this transaction a fraudulent transaction or not? What we have been able to do is completely eliminate that manual business process. So I think the next frontier of an application is the automation of business processes where historically technology tools have made humans better. What we're doing now is actually taking to the next level. We're automating processes that things like deep learning, artificial intelligence, algorithms, machine learning can automate and then taking business processes that take thousands of people and putting it down to tens of people. That is what an application is. An automation of a business process that is solving a particular problem. Is the platform viable today to make that happen? Absolutely. I think it is a, we have to understand and realize. And this is my biggest, biggest problem with the industry and the ecosystem. Problem number one, two big problems. And I'll vent over here for a little bit because you gave me the chance. theCUBE is working right down on the couch. We're happy to talk and make things comfortable for you. But I think the first issue is we will do a disservice to the big data industry as participants in the ecosystem by making Hadoop a storage platform. Hadoop is not a storage platform. It was built to be a computationally parallel computational engine. Number one. Number two, let's not forget that there are companies, incredibly profitable next generation companies who have architected new business models on Hadoop. So let's take their names. Google, Facebook, Yahoo. And I think Yahoo is back on an upswing. You know, even things like Microsoft, Twitter, LinkedIn, they have actually built brand new companies, business models, publicly-traded companies on Hadoop. So when someone says, Hadoop is an enterprise ready, are they telling me that Google with a $300 dollar market cap isn't an enterprise? Or LinkedIn and Twitter and Facebook aren't enterprises? So I think it's the biggest or the worst kept secret to call Hadoop not enterprise ready. Hadoop came out six years ago, enterprise ready. And it's always been enterprise ready. Let me push back on that a little bit. So those companies you mentioned, kind of had a Greenfield opportunity. They were built from scratch fairly recently. So how do you apply the technology in a way that's as easily accessible to a company like P&G or Bank of America or some company that's been around for a long time has a lot of legacy technology and it's got to manage that it's a change management issue among other things. So how do you go about easing that transition? So I think I'll take an example of a very important customer of ours, a couple of customers actually. I think this is where the convergence of many trends are helping ease the pain. So let me first agree with you. I completely agree. The transition is painful as they say, right? Rome wasn't built in a day. It took weeks because you had to deal with the legacy. I think it's a similar issue. So it's why it is incredibly painful. There's a massive convergence of certain trends that is making it not just easier, but an eventuality that has to happen. The three big trends that we are witnessing and you guys cover incredibly well are cloud, big data, and mobile. And the convergence of those three trends are making this transition into a application-focused business enterprise that is solving problems for their customers using data to make their lives better. At Tresera we have this philosophy that if a customer of ours and enterprise use our software, we want them to become customer advocates. We want them to make products and services that make the lives of their customers better. The fact that between cloud, big data, open source, and mobile, the economics of the transition is so much dramatically easier. So think of it. 10 years ago, when you had a transition from mainframe to client server, there was billions of dollars of transition. It doesn't, the economics for transitions are so much easier. The pace of innovation is so much more rapid and the acceptance of open source as an enterprise-ready technology platform, in general, so much more cleaner that the pain behind the transition is a lot less. It will take time. What we are seeing happen is the creation of new organizations in enterprises when they're all called these chief data office organizations that are helping highlight areas where the transition could be better. So we call it, get one quick win. Get one win to fund future wins. And we're seeing the start of companies picking business areas or problem challenges or business opportunities to find the early win on and then transition platforms. Surprisingly enough, Jeff, what's helping them is a traditional licensing model. The fact that software used to be sold in a perpetual license model and if you stop paying the maintenance fees, you still own the software. What they're saying is, I can stop paying for my legacy software, keep it running, not grow it, and then start offloading, not storage, but analytical workloads onto new technologies. And in a very ironic way, the perpetual licensing model, transition to a term licensing model, is helping ease the transition. Well, yeah, it'll take time. It'll take time. We were talking a little bit beforehand about how the sales motion has changed significantly in the software industry. Correct. Tell us a little bit about how you see that evolving and how that has evolved. I think the market is the best teacher, as we all say. And when we started to say that we made a big bet, we said, what will differentiate us is not going to be only technology, is not going to be only domain, and is not going to be only science. It'll be a combination of the three. You've heard me talk about it in the past. I think what we haven't spoken a lot about and we're seeing happen is a complete disintermediation of the existing technology sales cycle, where the back slapping and things that we don't need to say on air, sales activities that go on to sell technology just don't work anymore. What we are finding and realizing is the person, for example, at Truseta, who runs our financial services vertical, is a banker at heart and a technologist by training. So the ability to understand which combinations of technology algorithms in a particular business area can help deliver actionable insight and communicate that, not just to a technology buyer, not just to a business buyer, not just to a chief data officer, but a combination of the three is a very different skill. Here's the good news, it can work. What we have proven at Truseta now is if you can actually bring it together, even in an open source ecosystem, the value to be delivered to us as a software company is multi-seven figures. So if you can communicate the vision, if you can build the software and implement in delivering actionable insight in that tripartite sales conversation that has never existed before, with a different kind of salesperson, it can absolutely be done. But it's a big change. I'm surprised why there's not much being written. As much as you write about the stack being turned over, technology changing, economics changing, not many people are writing about the fact that sales model is fundamentally different. That's why large tech is struggling. They can't sell anymore. They're knocking on the door. No one answers the knock. So I got to talk to you. We've always talked about our crowd chat, almost like we're doing data science, the work you're doing. We're pioneering a lot of the big data. So I think there's some use cases out there where people have taken the platform from say Hortonworks or using social data like what we're doing. TrueCar was on yesterday showing some real innovation around having a clean sheet of paper. So I got to ask you, because you've been on both sides of the house. You've seen the legacy side at banks, the existing legacy, and you've got a clean sheet of paper with Trasada. Describe the differences, the two rows, and how does someone work in a green field, their clean sheet of paper, new venture? And how does someone work in a legacy to bring the new world into a legacy world? What are the challenges? What's the opportunity? I think the biggest, it's a phenomenal question. I think the biggest challenge, let's go to the legacy part first, John. The biggest challenge is finding a nugget and a team and someone with balls to take some risk. Take some, and I'm very serious about this, take some risk. Or make some bold moves that give you early wins. That's the biggest issue around legacy infrastructures not being quick enough for disruption. Because as is very well said, disruption happens. Whether you want it to happen or not, disruption happens. So I think the biggest lesson we have learned is it takes one person with a dream gene and a large legacy organization to say, I'm going to make a bet against one particular problem to prove that a new way of thinking, of doing things, can actually deliver value. If you can find the person with a dream gene and make sure the person is successful, it will work. On the green field of paper, I actually think starting a company in the current times is trickier in working in a big company, taking my call. Because when you take our call, we make your life easier. If you're a general officer at a large bank or a retailer, we've basically made your life easier by having solved what we call is the collect data, curate the data, compute the insight, convert the insight. We've already done that. I have been incredibly humbled as an entrepreneur in trying to figure out what are the right bets to make. As fast and fluid as the open source community is, it's also very tricky when ties change very quickly. Companies you think are not going to make it announce large amounts of funding and things change. I think making the right bets in open source, given the fact that open source will lead the world, not the software will lead the world, my twist, open source will lead the world, has been an incredibly hard, incredibly hard experience with great reward because I think we made some good bets and we figured out how to play in that domain. What's the biggest challenge you've had for being an entrepreneur, you're being nice about it? There are some rough days, it's a meat grinder. Yes. Because if you feel you could go out of business. Yes. If you're in a company, you get the posh funding. But as a startup, you've got to make tough calls. What has been the hardest challenge for you as an entrepreneur and how did you react to that adversity, share a story? I think there are tons of them. I remember talking to Christian Chabot in the first year of Tosita and saying, Christian, why is it that I feel one day that I rule the world and I had that dynamic moment that I want to stand on a ship and say, you know, I'm the king of the world. And the other thing I can't make payroll. And he says, he laughed. And he said, Abhi, for the first year of Tableau and we all know Tableau, we all love Tableau. I remember talking about Tableau in 2009 on theCUBE and you and Dave saying, what company is this? You know, and now we all know who Tableau is. And he says, bad hand ran and him throughout the first year was sitting in the parking lot and had the same conversation. Are we going to make it? The trickiest conversations for me have been the people, have the people conversations. You know, finding the right talent and having them buy into the passion and the vision as much as we believe it. Surprisingly enough, the customer part has been easy. The customers we've gone to, we had our first customer in our first year. We are cash flow positive as a company in two years of operations, you know. We have doubled our capital. We have tripled our company. So you look at the customer part being easy but finding and hiring talent that can sit with you and you know, I have a saying at Tresera when we sit down and talk about, they'll say, Abhi's your company, I said, no, it's our company. Finding people with the same passion to make a dent in the world, to change the world. We fundamentally believe at Tresera, John, that we are rewriting the book and enterprise software. That the way enterprise software will be written, delivered and sold is being done successfully at Tresera today. And you and I will sit here five years from now and say, Abhi, what did you do? And I'll say, I have no idea. But we had a very strong vision. So is it DevOps focused? Is it more SaaS? What is the new enterprise? No, I think it's having a very clear vision. I think we are one of few companies in the three years you've known us. We haven't pivoted. You've never seen me use anything except the original vision and idea. We have stayed so focused on the original vision in spite of all the diversions. And we know it. I got to say, you and Rob Bearden have been absolutely clear every time in theCUBE, there's been no body sort of it's the same vision you're executing your original idea. And you're doing well. And that's been the hardest because when you are not doing well and you are being quoted to raise money and you have smart people telling you, but this hasn't worked before. I think the challenge I've had is not many people in the money giving community and the money making community, I believe the clients, truly understand what enterprise software in the future will look like. No one has a clue. They want to recreate databases and tools and BI in Hadoop. All that is commodity. When you don't have a clue, it becomes very tricky on which people you listen to or not. And that I would say is probably been the hardest, John, is staying focused on the vision when the future is unclear. But I think that's what has been hard of it's would say, that is the hard thing about hard things. It's been a phenomenal, we are proud that I can still sit over here with the two of you, have the ability to sponsor Silicon Angle, which has been always, as I said, the first thing we will ever, ever write a check to is you guys. And sit and have a conversation on the success we've had. Because it's been hard days. You know, we get a lot of feedback, people say we should like do more selling out. And we want to don't want, we want sponsorships, we want to get the right people. You've been a great supporter. And you know what? We believe in transparency and that's why theCUBE exists. We want to make it accessible for everybody. And we could make more money, but we don't because it changes the game. So, we've lived that with you. Absolutely. And what I find challenging is, staring down people who have potentially, but might look like a better deal. Oh, take the money over here. What you're saying is, you had to make those choices. The conventional wisdom was, that's never worked before, but I got a bag of money come this way and I'll fund it because we were funding that sector. Correct. You say, no, that's not the vision we have. How hard is that? Very. Have you waffle 50-50 and then say, no. John, incredibly. I think I'll tell you what is harder. I'm surprised as an entrepreneur, as how many, why there is such a big focus in the valley and the larger startup community on how much money you raise versus how much money you make. Trasita, in essence, had a series around with our customers. You guys reported our numbers. We did a year last year that we signed $10 million worth of business. That was our series A. We didn't give any equity up. We didn't dilute any shareholders. But we, in essence, have spent that much money in building Trasita. It is incredibly hard, not just to say no to bags of money who want to invest in you, but take them in their direction. You can't imagine how many people have come to us and said, well, maybe you should build a database company. Maybe you should build a BI company. You should do more visualization. We're like, no, no, and no. But it's harder with the customers. When customers come to you with a bag of cash and say, but what I really need is this vision. And that is, I think, our test. It's saying no and saying no. That is not- Product market fit when customers are paying for your product is absolutely value. And I will say this on the record, and this is my maybe old school view. The, how much money you raise is not the benchmark for entrepreneurial success. A lot of the young kids think, oh, I raised a big VC route, I've made it. What they don't know is that's the start line. And you've got dynamics that you've inherited for the money that you may or may not even need. So the true entrepreneur are the ones who can maintain control of the company and do no financing. But if you do a venture round, maintain control. Absolutely. Because you can be creative, you can control the culture, the founders can stay around or leave, but you're not going to get booted. So the fear is, that's the fear. But like, I just say, what with your wallet? If you can scale a company, self-funded with customer cash flow, it's equity free capital. Absolutely. I say, I tell every entrepreneur, revenue is the cheapest form of capital. And I think that's my point. I think big data, let's go back to, you know, the big data subject, John and Jeff. Big data with the open source underpinnings finally provides every entrepreneur the opportunity to get to cash quickly. I am incredibly surprised why we are funding big data startups. Leave aside the infrastructure distribution companies, other analytical companies don't need hundreds of millions of dollars to build predictive analytics applications. Because if you are truly building predictive analytics applications, your average deal size is multi-million dollars. You don't need 20 million dollars to build a company. You don't. Here's my thing. I'm going to say this again, being bold. Since we're being bold, I'll vent a little bit. If you're an entrepreneur and you can't build a product and generate sales, you're not worthy to start a company. I agree. If you are in the SaaS cloud open source world, your tools and paint brushes are free. And if you can't paint at least a minor Picasso or a small piece of art and can't get anything for it, don't even start a company. Go work for the big company. Completely agree. Why is everyone engineer their time to get VC funding? Show some traction. Absolutely. Show some sales, show some mojo. That to me is the test. Now, if you're building a fab plant or a clean stack venture, car company, no problem. Do the prototype, raise a boatload of money, get a partner. I think it's been very hard, but I will say it's also reassuring because it has given us the luxury as three industry participants to talk about what do big data technology software companies look like in the future? And I would love to sit down with you, Jeff, and talk about the architecture of the company, not just our software, because we have our salespeople, our domain experts, and they're talking to CMOs and CROs, and we should run it through what our sales cycles look like and how they've shrunk from six months to six weeks and how we build, test, deploy our software incredibly rapidly. And I think in that is the nuggets of what do those companies in the future look like? Well, you've got to be able to speak the language of business, not just the language of technology. If you're selling to an end user essentially, a C-level executive who wants to get a problem solved, they don't want to hear about MapReduce and Scoop and all that stuff. So you've got to be able to speak to them on a level that resonates with them and that's about solving a problem that's going to either save them money or make them money. It's pretty simple. Absolutely. And move their business forward. If you can do that and your product can deliver, then you've got something. Exactly. And it's interesting. I would love to get your take, it sounds like you've mentioned some of the tools that companies are kind of starting to go poof. They will go poof. If they haven't gone poof, they're going to go poof. Well, so my question is, do you feel like, and related to what John's point about, you know, raising all this money, especially in the big data space is pretty easy. It's just, yeah, I've got a big data company. Okay, here's $10 million. Do you think people are getting into this for the wrong reasons? They're getting into this to create, all right, I've got a decent technology, I'm going to raise a bunch of money and I'm going to sell it to one of these big whales out here who are desperate, clutching at straws to somehow get their own big data strategy, some of them frankly don't understand the market at all. Is that happening or what's the dynamic? You know, you probably know it better than I do, but I'll give you my perspective on Truseta. We're building Truseta for the long term. Whether that's an IPO, since day one, we have never thought that Truseta's takeout is not a company. Or let's make Truseta attractive that someone has to look at it and go, oh well, you have, so you hit the metrics, you have X number of salespeople, you're wide developers, you're in Z markets. I don't care if you're losing money, you fit the box for us to come acquire you, right? We have never built it that way. I think you raise a very interesting point though, which is what are people priming the company for? And I think the answer, in our opinion, is why people don't understand that tools and infrastructure will get commoditized, baffles me. What it tells me is there are certain books written around how you build technology companies around a particular stack-like concept that need to be rewritten, but no one's rewritten it yet. They're out of date. They're out of date. No one knows what the future actually looks like. They're all trying to approximate it. And that's where I think our bet is the most interesting. So I fundamentally do believe that if you are building a tool company, it will not work. If you're not building something around build analytics on a stack that fundamentally is open source, it will not work. If you cannot add, and I think that you mentioned those words, talk to a business user, deliver for a business user. I think the most important part over there is everybody is skeptical. Everybody is skeptical that you can take business processes and you can automate the last mile in technology. Because historically, it could not have been automated at scale and with the right economics. But it can be now. What does that look like? Nobody knows. I think that's the white space we want to play in. The little gray areas of the nooks and crannies where people want to hide, it doesn't interest us. So BI visualization, dashboarding, transformations, cleaning, curation, good luck. We wish you the best. We give it away for free. So if anybody, any company wants to get a data transformation toolkit, we give it for free. Don't buy it. Well, I think it's important for people to understand. You're not saying those things aren't important. They're very important. They're critically important. They're critically important. But that's not how you, in this new world, that's not how you're going to deliver value and build a company. Absolutely, not to mention in the collect data, curate the data, aka process transform it, compute the insight and convert the insight. You can't piecemeal that process. Every analytical application has to do all those four activities within the application. So you can't say, I'm building a company to collect data. I'm building a company to just curate the data. It doesn't work that way. People, logical human beings don't think that way. Business processes don't work that way. So it's incredibly hard to take that logical cycle of taking raw data and monetizing insight and doing it piecemeal with multiple vendors. It doesn't work. Which applies to what's going on here in the Hadoop ecosystem, because it's very much, you take a company like Hortonworks. They're very much partner-centric. Absolutely. And bringing on all the different components from different vendors, which is why we're seeing so many partnerships that are really investing in engineering partnerships. Really working together on the ground to get them to work together, because as you say, it's got to be as seamless as possible. So that's one of the challenges in a market like this, I think. It is, but I think those partnerships are a very short-term focused thing. We have said before, I'm very mortal in my comments, but ETL is dead. We won't say that, but ETL is free. ETL is free, it's free, it's free. We need more time on the queue. We got to get to the dirty data conversation. ETL is free, BI is free, you know? Data transformation is free, metadata is free. There's H Catalog, you know? There's Driven by Cascade. Those basic database-oriented functions are functions. You can't build companies around. There are commodities forever. So give it up, and let's go to the next level where you can bring it all together seamlessly. You can't keep moving there. This is like repeating our conversation from four years ago. You can't move data back and forth. One Hadoop is a storage, processing, analysis, and visualization platform, all in one. Why we don't say it more often? Why we don't imbibe that as a business model? Well, you know, I guess we do. I've got to ask you what we've got running out of time here. Are the folks that are attending the conferences get the three buckets, the minnows, the tuners and the whales, the minnows are the startups through Series B funding, and then everyone from Series C funding to pre-IPO, the tuners, and then IPO, big companies, the whales. Yes. Who wins and who loses in those categories? In each bucket, what do the people have to do to succeed and if they don't do that, they'll lose. So startups, growing companies, and public. In each category, what are the pitfalls? What are the critical traps and what do people need to be successful in each theater? So I think this will be the, I guess the shortest answer I've ever given you, John, which is give me a pack of piranhas versus a whale. Guess what, I'll always pick a pack of piranhas. Just scale out commodity hardware, a bunch of piranhas. I will always pick because a slow moving whale in front of a pack of piranhas, it only ends one way. You know, and there's blood in the water, it only ends one way. This is not complimentary, hats off to your most recent research that I'm dying to read around the points that this is a replacement for the technology stack. It's not a complimentary stack. It's a replacement. Well, I said that early on, Jeff slapped me down a little bit, so the numbers weren't that high in the adoption on that number. But it's very clear that the trend line is clearly going towards a replacement. Absolutely. And clearly. I think people don't want to talk about it right now because it's one of those things where, you know, someone's on life support, like, hey, no, he's going to make it. Come on, it's going to happen. We're going to cheer for it, but come on. We see a cliff coming. Absolutely. Our numbers are clearly trending that way. The reason I corrected you was because it's not showing that definitively yet. Frankly, there's a lot of... No, I know, I was over the top. There's a lot of, look, there's a huge industry and a lot of the players are behind us who have a very vested interest in making that argument. Absolutely. And that messaging is getting through to customers. Look, I think I'll only say one thing. If you follow stock prices, which I'm sure everybody does, there's a reason why large tech is on a spiral. It's not because open source is killing it. It is fundamentally because the sales process, how technology is built, delivered, and sold. All three is completely different. If you want to see what that looks like, that's what I truly believe. If you have a humble start at Prasada to prove that next-gen model, I think we're doing a phenomenal job executing and what that future looks like. Great to see you here, you're on the Cube. I mean, we can go for another hour, but I want to get your lap. I want you to share with the folks out there, because we've been talking about this from day one and you've been pretty much right on all your predictions, and you're in the trenches building a company. What is the big takeaway from this year, from your perspective, looking at the landscape and the movement of the players here? Over the past year to this year, what's happened and what will happen the next short term, near term, say next six to eight months? I think two major trends, John. One is I get asked the question a lot, given the fact that we've grown up on the East Coast and have a financial background. Are we in a bubble? And Mark Andreessen's spoken about it. I think you will see a coming to earth of valuations. I was looking at numbers yesterday and Splunks had a sub-4 billion market cap. Tableau is at a sub-4 billion market cap and Claretta got valued at 4.2 billion in the private markets. So I think you will see a much smarter movement of money towards disruptors that will get valued very aggressively, but reasonably. There's something for us to, there's a canary in the coal mine when IPOs are box and square store and we should all be very cognizant of it. As my lawyer in the West Coast reminds me, last time there was a bubble, there were two things that define it in Silicon Valley. Traffic on 101 and real estate prices. I hear both those things are heard in the wrong direction again. So I think that's something to watch out for. I think from an adoption cycle, we will see a dramatic increase in reduction of IT budgets with large corporates being replaced with much more scalable economical technologies. So I think fundamentally, the top lines of large tech players are under massive attack and you will see that transform rather quickly into larger contracts and deals for companies like ours, but on a magnitude, it's going to be, you know, a multi-use lower than what we have been used to seeing in large tech. I think those are both two defining trends. You will see the pack of Perhanas move very quickly. Perhanas are there and they're dangerous in the herd and that's big data. It's all about the data everywhere. Thanks for coming on. Congratulations on your success. You're a tech athlete, you know, self-funded, customer-funded, great value proposition. An example, then I'm going to look back 10 years. Remember when, you know, 10 years, it's a 10-year cycle. You know, I have to say something. It's the vision, the support and what the two of you and SiliconANGLE, Wikibon, the cube do for entrepreneurs is invaluable. The voices you have made heard of someone like myself, when three years ago, we announced to sit on the cube. It is what you are doing for the entrepreneurial community is invaluable to make the Perhanas swifter. So thank you for that and thanks to our customers. We would not be, we wouldn't have this confidence were it not for our customers agreeing with us in our vision. So thank you for everything the cube does for entrepreneurs. I got to tear my eye because it means a lot to me to hear you say that it's truly what we strive for, strive to see the noise and it's about transparency. You know, we get blocked a lot. Believe me, you know, O'Reilly Media doesn't want us that had dupe world, that's clear. But you know what? We will do whatever it takes to make, get the word out. We've got the crowd chat now, engaged out there. Open source content is about enabling people to collaborate and that's always been an amazing business model. Creates massive change. You're a part of it. Glad to have you support us. Thank you so much. As Ron Burgundy said, 24 Hour Sports was a bad idea, you know? They look back at 24 Hour of Tech TV and say the same thing. Hey, we could be a VC firm someday. Here all these bloggers are moving into becoming venture capitalists these days. Yes they are, yes they are. Get a blog job, be in the cube. Next you know you're a CEO or a venture capitalist. This the cube, we write back from an exciting activity here. We'll be right back after the short break.